A dual-linear predictor approach to blind source extraction for noisy mixtures

W. Liu, D. Mandic, A. Cichocki
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引用次数: 7

Abstract

A second-order statistics based dual-linear predictor structure is proposed for blind source extraction from noisy instantaneous mixtures. The noise component is assumed to be spatially and temporally white, but the variance information of noise is not required. A detailed proof of the proposed approach is provided and an adaptive algorithm is developed. Simulation results show that it can extract the source signals successfully.
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噪声混合源盲提取的双线性预测方法
提出了一种基于二阶统计量的双线性预测器结构,用于噪声瞬时混合的盲源提取。假设噪声分量在空间和时间上都是白色的,不需要噪声的方差信息。给出了该方法的详细证明,并开发了一种自适应算法。仿真结果表明,该方法能够成功地提取出源信号。
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A dual-linear predictor approach to blind source extraction for noisy mixtures Optimal combination of fourth order statistics for non-circular source separation Blind channel identification and signal recovery by confining a component of the observations into a convex-hull of minimum volume Power-aware distributed detection in IR-UWB sensor networks Linear least squares based acoustic source localization utilizing energy measurements
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